» Articles » PMID: 31573946

Design Process and Utilization of a Novel Clinical Decision Support System for Neuropathic Pain in Primary Care: Mixed Methods Observational Study

Overview
Journal JMIR Med Inform
Publisher JMIR Publications
Date 2019 Oct 2
PMID 31573946
Citations 7
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Computerized clinical decision support systems (CDSSs) have emerged as an approach to improve compliance of clinicians with clinical practice guidelines (CPGs). Research utilizing CDSS has primarily been conducted in clinical contexts with clear diagnostic criteria such as diabetes and cardiovascular diseases. In contrast, research on CDSS for pain management and more specifically neuropathic pain has been limited. A CDSS for neuropathic pain has the potential to enhance patient care as the challenge of diagnosing and treating neuropathic pain often leads to tension in clinician-patient relationships.

Objective: The aim of this study was to design and evaluate a CDSS aimed at improving the adherence of interprofessional primary care clinicians to CPG for managing neuropathic pain.

Methods: Recommendations from the Canadian CPGs informed the decision pathways. The development of the CDSS format and function involved participation of multiple stakeholders and end users in needs assessment and usability testing. Clinicians, including family medicine physicians, residents, and nurse practitioners, in three academic teaching clinics were trained in the use of the CDSS. Evaluation over one year included the measurement of utilization of the CDSS; change in reported awareness, agreement, and adoption of CPG recommendations; and change in the observed adherence to CPG recommendations.

Results: The usability testing of the CDSS was highly successful in the prototype environment. Deployment in the clinical setting was partially complete by the time of the study, with some limitations in the planned functionality. The study population had a high level of awareness, agreement, and adoption of guideline recommendations before implementation of CDSS. Nevertheless, there was a small and statistically significant improvement in the mean awareness and adoption scores over the year of observation (P=.01 for mean awareness scores at 6 and 12 months compared with baseline, for mean adoption scores at 6 months compared with baseline, and for mean adoption scores at 12 months). Documenting significant findings related to diagnosis of neuropathic pain increased significantly. Clinicians accessed CPG information more frequently than they utilized data entry functions. Nurse practitioners and first year family medicine trainees had higher utilization than physicians.

Conclusions: We observed a small increase in the adherence to CPG recommendations for managing neuropathic pain. Clinicians utilized the CDSS more as a source of knowledge and as a training tool than as an ongoing dynamic decision support.

Citing Articles

Analytical validation of Exandra: a clinical decision support system for promoting guideline-directed therapy of type-2 diabetes in primary care - a collaborative study with experts from Diabetes Canada.

Grechuta K, Shokouh P, Bayer V, Kraemer H, Gilbert J, Jin S BMC Med Inform Decis Mak. 2025; 25(1):74.

PMID: 39939992 PMC: 11816501. DOI: 10.1186/s12911-025-02881-4.


Benefits of Clinical Decision Support Systems for the Management of Noncommunicable Chronic Diseases: Targeted Literature Review.

Grechuta K, Shokouh P, Alhussein A, Muller-Wieland D, Meyerhoff J, Gilbert J Interact J Med Res. 2024; 13:e58036.

PMID: 39602213 PMC: 11635333. DOI: 10.2196/58036.


Optimizing the design and implementation of question prompt lists to support person-centred care: A scoping review.

Ramlakhan J, Dhanani S, Berta W, Gagliardi A Health Expect. 2023; 26(4):1404-1417.

PMID: 37227115 PMC: 10349246. DOI: 10.1111/hex.13783.


Usability of the IDDEAS prototype in child and adolescent mental health services: A qualitative study for clinical decision support system development.

Clausen C, Leventhal B, Nytro O, Koposov R, Rost T, Westbye O Front Psychiatry. 2023; 14:1033724.

PMID: 36911136 PMC: 9997712. DOI: 10.3389/fpsyt.2023.1033724.


Barriers and Facilitators to the Use of Clinical Decision Support Systems in Primary Care: A Mixed-Methods Systematic Review.

Meunier P, Raynaud C, Guimaraes E, Gueyffier F, Letrilliart L Ann Fam Med. 2023; 21(1):57-69.

PMID: 36690490 PMC: 9870646. DOI: 10.1370/afm.2908.


References
1.
Khairat S, Marc D, Crosby W, Al Sanousi A . Reasons For Physicians Not Adopting Clinical Decision Support Systems: Critical Analysis. JMIR Med Inform. 2018; 6(2):e24. PMC: 5932331. DOI: 10.2196/medinform.8912. View

2.
Kortteisto T, Komulainen J, Makela M, Kunnamo I, Kaila M . Clinical decision support must be useful, functional is not enough: a qualitative study of computer-based clinical decision support in primary care. BMC Health Serv Res. 2012; 12:349. PMC: 3508894. DOI: 10.1186/1472-6963-12-349. View

3.
Roshanov P, You J, Dhaliwal J, Koff D, Mackay J, Weise-Kelly L . Can computerized clinical decision support systems improve practitioners' diagnostic test ordering behavior? A decision-maker-researcher partnership systematic review. Implement Sci. 2011; 6:88. PMC: 3174115. DOI: 10.1186/1748-5908-6-88. View

4.
Gilron I, Watson C, Cahill C, Moulin D . Neuropathic pain: a practical guide for the clinician. CMAJ. 2006; 175(3):265-75. PMC: 1513412. DOI: 10.1503/cmaj.060146. View

5.
Trafton J, Martins S, Michel M, Lewis E, Wang D, Combs A . Evaluation of the acceptability and usability of a decision support system to encourage safe and effective use of opioid therapy for chronic, noncancer pain by primary care providers. Pain Med. 2010; 11(4):575-85. DOI: 10.1111/j.1526-4637.2010.00818.x. View